Python 2.0 was released on 16 October 2000, with many major new features including a full garbage collector and support for unicode. However, the most important change was to the development process itself, with a shift to a more transparent and community-backed process.[4] Python 3.0, a major, backwards-incompatible release, was released on 3 December 2008[5] after a long period of testing. Many of its major features have also been backported to the backwards-compatible Python 2.6 and 2.7.[6]

In February 1991, Van Rossum published the code (labeled version 0.9.0) to alt.sources.[7] Already present at this stage in development were classes with inheritance, exception handling, functions, and the core datatypes of list, dict, str and so on. Also in this initial release was a module system borrowed from Modula-3; Van Rossum describes the module as "one of Python's major programming units".[1] Python's exception model also resembles Modula-3's, with the addition of an else clause.[3] In 1994 comp.lang.python, the primary discussion forum for Python, was formed, marking a milestone in the growth of Python's userbase.[1]

Python reached version 1.0 in January 1994. The major new features included in this release were the functional programming tools lambda, map, filter and reduce. Van Rossum stated that "Python acquired lambda, reduce(), filter() and map(), courtesy of a Lisp hacker who missed them and submitted working patches".[9]

During Van Rossum's stay at CNRI, he launched the Computer Programming for Everybody (CP4E) initiative, intending to make programming more accessible to more people, with a basic "literacy" in programming languages, similar to the basic English literacy and mathematics skills required by most employers. Python served a central role in this: because of its focus on clean syntax, it was already suitable, and CP4E's goals bore similarities to its predecessor, ABC. The project was funded by DARPA.[11] As of 2007[update], the CP4E project is inactive, and while Python attempts to be easily learnable and not too arcane in its syntax and semantics, reaching out to non-programmers is not an active concern.[12]

In 2000, the Python core development team moved to BeOpen.com to form the BeOpen PythonLabs team. CNRI requested that a version 1.6 be released, summarizing Python's development up to the point at which the development team left CNRI. Consequently, the release schedules for 1.6 and 2.0 had a significant amount of overlap.[4] Python 2.0 was the only release from BeOpen.com. After Python 2.0 was released by BeOpen.com, Guido van Rossum and the other PythonLabs developers joined Digital Creations.

The Python 1.6 release included a new CNRI license that was substantially longer than the CWI license that had been used for earlier releases. The new license included a clause stating that the license was governed by the laws of the State of Virginia. The Free Software Foundation argued that the choice-of-law clause was incompatible with the GNU GPL. BeOpen, CNRI, and the FSF negotiated a change to Python's free software license that would make it GPL-compatible. Python 1.6.1 is essentially the same as Python 1.6, with a few minor bug fixes, and with the new GPL-compatible license.[13]

Python 2.0 introduced list comprehensions, a feature borrowed from the functional programming languages SETL and Haskell. Python's syntax for this construct is very similar to Haskell's, apart from Haskell's preference for punctuation characters and Python's preference for alphabetic keywords. Python 2.0 also introduced a garbage collection system capable of collecting reference cycles.[4]

Python 2.1 was close to Python 1.6.1, as well as Python 2.0. Its license was renamed Python Software Foundation License. All code, documentation and specifications added, from the time of Python 2.1's alpha release on, is owned by the Python Software Foundation (PSF), a non-profit organization formed in 2001, modeled after the Apache Software Foundation.[13] The release included a change to the language specification to support nested scopes, like other statically scoped languages.[14] (The feature was turned off by default, and not required, until Python 2.2.)

A major innovation in Python 2.2 was the unification of Python's types (types written in C) and classes (types written in Python) into one hierarchy. This single unification made Python's object model purely and consistently object oriented.[15] Also added were generators which were inspired by Icon.[16]

Python 3.0 (also called "Python 3000" or "Py3K") was designed to rectify certain fundamental design flaws in the language (the changes required could not be implemented while retaining full backwards compatibility with the 2.x series, which necessitated a new major version number). The guiding principle of Python 3 was: "reduce feature duplication by removing old ways of doing things".

Python 3.0 was developed with the same philosophy as in prior versions. However, as Python had accumulated new and redundant ways to program the same task, Python 3.0 had an emphasis on removing duplicative constructs and modules, in keeping with "There should be one— and preferably only one —obvious way to do it".

Python 3.0 was released on December 3, 2008.[5] The Python 2.x and Python 3.x series were planned to coexist for several releases in parallel, with the 2.x series existing largely for compatibility and with some new features being backported from the 3.x series.[6] Python 2.6 was released to coincide with Python 3.0, and included some features from that release, as well as a "warnings" mode that highlighted the use of features that were removed in Python 3.0.[17] Similarly, Python 2.7 coincided with and included features from Python 3.1,[18] which was released on June 26, 2009. Python 2.7 was the last release in the 2.x series;[19] parallel releases ceased as of Python 3.2.

Python 3.0 broke backward compatibility. There was no requirement that Python 2.x code would run unmodified on Python 3.0. There were basic changes such as changing the print statement into a print function (so any use of print as a statement will cause the program to fail), and switching to Unicode for all text strings. Python's dynamic typing combined with the plans to change the semantics of certain methods of dictionaries, for example, made perfect mechanical translation from Python 2.x to Python 3.0 very difficult. However, a tool called "2to3" could do most of the job of translation, pointing out areas of uncertainty using comments or warnings. Even in an alpha stage, 2to3 appeared to be fairly successful at performing the translation.[20] For projects requiring compatibility with both the 2.x and 3.x series, the Python development team recommended keeping one source (for the 2.x series), and producing releases for the Python 3.x platform using 2to3. Edits to the Python 3.x code were discouraged for so long as the code needed to run on Python 2.x.[6]

Changing print so that it is a built-in function, not a statement. This made it easier to change a module to use a different print function, as well as making the syntax more regular. In Python 2.6 and 2.7 this can be enabled by entering from __future__ import print_function.[21]

Moving reduce (but not map or filter) out of the built-in namespace and into functools (the rationale being that operations using reduce are expressed more clearly using an accumulation loop);[22]

Adding support for optional function annotations that can be used for informal type declarations or other purposes;[23]

Unifying the str/unicode types, representing text, and introducing a separate immutable bytes type; and a mostly corresponding mutable bytearray type, both of which represent arrays of bytes;[24]

Python's core syntax and certain aspects of its philosophy are directly inherited from ABC. C provided some of Python's syntax, and the Bourne shell served as the model for an interpreter that becomes interactive when run without arguments.[25] List comprehensions, anonymous functions, lexical closures and the map function are among the major features borrowed from functional languages, primarily dialects of Lisp and Haskell.[4][9][14] Generators and iterators were inspired by Icon, and were then fused with the functional programming ideas borrowed into a unified model.[16]Modula-3 was the basis of the exception model and module system.[1][3]Perl lent Python regular expressions, used for string manipulation.[26] Python's standard library additions and syntactical choices were strongly influenced by Java in some cases: the logging package,[27] introduced in version 2.3,[28] the threading package for multithreaded applications,[29] the SAX parser, introduced in 2.0, and the decorator syntax that uses @,[30] added in version 2.4.[31] Python's method resolution order was changed in Python 2.3 to use the C3 linearization algorithm as used in Dylan.[32]

^A.M. Kuchling (2010-07-03). "What’s New in Python 2.7". Retrieved 2012-10-07. Much as Python 2.6 incorporated features from Python 3.0, version 2.7 incorporates some of the new features in Python 3.1. The 2.x series continues to provide tools for migrating to the 3.x series.